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Published on: March 27, 2018
Preoperative nonlinear behavior in heart rate variability predicts morbidity and mortality after coronary artery
Moacir Fernandes de Godoy1, Isabela Thomaz Takakura, Paulo Rogério Correa
1Sao Jose do Rio Preto Medical School, FAMERP, Sao Jose do Rio Preto, Sao Paulo, Brazil.
Insights
Reduced nonlinear heart rate variability (HRV) before coronary artery bypass graft (CABG) surgery is linked to increased postoperative complications and mortality. Nonlinear HRV analysis may serve as a new prognostic tool for high-risk patients undergoing major surgery.
Area of Science:
- Cardiology
- Medical Technology
- Data Science
Background:
- Reduced nonlinear heart rate variability (HRV) in the preoperative period is hypothesized to correlate with increased morbidity and mortality following coronary artery bypass graft (CABG) surgery.
- Investigating preoperative HRV nonlinear dynamics offers potential for identifying patients at higher risk for adverse postoperative outcomes.
Purpose of the Study:
- To demonstrate that diminished nonlinear behavior in preoperative heart rate variability (HRV) predicts higher morbidity and mortality rates in patients undergoing coronary artery bypass graft (CABG) surgery.
- To explore the utility of nonlinear HRV analysis as a prognostic tool for patients undergoing major elective surgeries.
Main Methods:
- Seventy patients undergoing CABG were enrolled, with HRV data captured using a Polar Advanced S810 heart rate monitor.
- Nonlinear HRV variables, including detrended fluctuation analysis (DFA), autocorrelation (tau), Lyapunov exponent (LE), and Poincaré plot (PP) parameters (SD1, SD2), were analyzed.
- Outcomes were evaluated based on two scenarios: death vs. non-death and postoperative events vs. their absence, assessing neurological complications, infections, kidney failure, arrhythmia, and mortality.
Main Results:
- Significant differences in DFA, alpha-2, LE, PP[SD1], and PP[SD2] were observed between death and non-death groups (p<0.05).
- Significant differences in alpha-1, alpha-2, tau, LE, PP[SD1], and PP[SD2] were found when comparing event occurrence (p<0.05).
- The Poincaré plot parameter PP[SD1] demonstrated the highest area under the ROC curve (0.78) in predicting mortality.
Conclusions:
- Preoperative nonlinear HRV analysis can identify patient subgroups at high risk for postoperative complications following elective CABG surgery.
- Specific nonlinear HRV variables, such as LE and PP[SD1], show promise as prognostic indicators.
- Nonlinear HRV analysis may evolve into a valuable prognostic tool for assessing patients scheduled for various major surgical procedures.
Background:
The aim was to demonstrate that a reduction in the nonlinear behavior of heart rate variability (HRV) in the preoperative period in patients undergoing coronary artery bypass graft (CABG) triggers higher morbidity and mortality rates in the postoperative stay.
Material/Method:
Seventy patients (59+/-10.3 years) were included. HRV was captured by a Polar Advanced S810 heart rate monitor and analyzed using the nonlinear variables detrended fluctuation analysis (DFA), autocorrelation (tau), Lyapunov exponent (LE), and the Poincaré plot (PP). Based on two scenarios, death vs. non-death (scenario 1) and events vs. their absence (scenario 2), the occurrence of neurological complications, infections, kidney failure, arrhythmia, and death were evaluated. Sensitivity, specificity, positive predictive value, negative predictive value, and odds ratio (95% CI) were recorded.
Results:
In scenario 1, significant differences were found for DFA, alpha-2, LE, PP[SD1], and PP[SD2], with p-values of 0.0172, 0.0343, 0.0159, 0.0069, and 0.0287, respectively. In scenario 2, differences were found for alpha-1, alfa-2, tau, LE, PP[SD1], and PP[SD2], with p-values of 0.0066, 0.0426, 0.0188, 0.0108, 0.0005, and 0.0158, respectively. The best areas under ROC curve were seen in scenario 1, with values of 0.72 (tau), 0.77 (LE), and 0.78 (PP[SD1]).
Conclusions:
Analysis of HRV in the nonlinear domain in the preoperative period in patients undergoing elective CABG surgery may detect subgroups with a high risk for postoperative complications, at least with the assistance of some of the variables, and it can become a new prognostic tool for assessing patients scheduled to undergo other major surgeries.
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